Publications#

Papers acknowledging DeepESDL#

Bao, S., Alonso, L., Wang, S., Gensheimer, J., De, R., & Carvalhais, N. (2023). Toward Robust Parameterizations in Ecosystem-Level Photosynthesis Models. Journal of Advances in Modeling Earth Systems, 15(8), e2022MS003464. https://doi.org/10.1029/2022MS003464

Estupinan‐Suarez, L. M., Mahecha, M. D., Brenning, A., Kraemer, G., Poveda, G., Reichstein, M., & Sierra, C. A. (2024). Spatial patterns of vegetation activity related to ENSO in northern South America. Journal of Geophysical Research: Biogeosciences, 129(1), e2022JG007344. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022JG007344

Martinuzzi, F., Mahecha, M. D., Camps-Valls, G., Montero, D., Williams, T., & Mora, K. (2024). Learning extreme vegetation response to climate forcing: A comparison of recurrent neural network architectures. Nonlinear Processes in Geophysics, 31, 535-557. https://npg.copernicus.org/articles/31/535/2024/#section14

Montero, D., Aybar, C., Mahecha, M. D., Martinuzzi, F., Söchting, M., & Wieneke, S. (2023). A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research. Scientific Data, 10(1), 197. https://doi.org/10.1038/s41597-023-02096-0

Montero, D., Kraemer, G., Anghelea, A., Aybar, C., Brandt, G., Camps-Valls, G., Cremer, F., Flik, I., Gans, F., Habershon, S., Ji, C., Kattenborn, T., Martínez-Ferrer, L., Martinuzzi, F., Reinhardt, M., Söchting, M., Teber, K., & Mahecha, M. D. (2024). Earth System Data Cubes: Avenues for advancing Earth system research. Environmental Data Science, 3, e27. https://doi.org/10.1017/eds.2024.22

Peters, J., Neumann, A., Jaeger, M., Gienapp, L., & Umlauft, J. (2025). ml4xcube: Machine Learning Toolkits for Earth System Data Cubes. Proceedings of the AAAI Conference on Artificial Intelligence, 39(27), Article 27. https://doi.org/10.1609/aaai.v39i27.35051

Söchting, M., Mahecha, M. D., Montero, D., & Scheuermann, G. (2023). Lexcube: Interactive visualization of large earth system data cubes. IEEE Computer Graphics and Applications, 44(1), 25-37. https://ieeexplore.ieee.org/abstract/document/10274107, IEEE Best PaperAward 2024 in Computer Graphics & Applications.

Weynants, M., Ji, C., Linscheid, N., Weber, U., Mahecha, M. D., & Gans, F. (2024). Dheed: An ERA5 based global database of dry and hot extreme events from 1950 to 2022. Earth System Science Data Discussions, 1–31. https://doi.org/10.5194/essd-2024-396

Zimmer, C., Neumann, A., Mahecha, M. D., & Umlauft, J. (2025). PATCH-FILL: Multiscale Gap-Filling for Earth System Data Cubes. IEEE Transaction on Geoscience and Remote Sensing, 63. 1.13 https://ieeexplore.ieee.org/document/11097902/references#references

Citations#

Rocha, J. C. (2022). Ecosystems are showing symptoms of resilience loss. Environmental Research Letters, 17(6), 065013. https://doi.org/10.1088/1748-9326/ac73a8

“… used as proxies of primary productivity of marine and terrestrial ecosystems. These variables have been harmonized by the Earth System Data Lab, so all data layers share the same time (weekly) and spatial (0.25 degree) resolution [32]. ”

Díaz, E., Adsuara, J. E., Martínez, Á. M., Piles, M., & Camps-Valls, G. (2022). Inferring causal relations from observational long-term carbon and water fluxes records. Scientific Reports, 12(1), 1610. https://doi.org/10.1038/s41598-022-05377-7

“… In particular, we use six different biosphere and atmosphere global gridded products, which are collected and curated in the Earth System Data Lab (ESDL). “

Papers reporting on DeepESDL#

Basel, A. M., Nguyen, K. T., Arnaud, E., & Craparo, A. C. W. (2023). The foundations of big data sharing: A CGIAR international research organization perspective. https://doi.org/10.3389/fenvs.2023.1107393

Sudmanns, M., Augustin, H., Killough, B., Giuliani, G., Tiede, D., Leith, A., Yuan, F., & and Lewis, A. (2023). Think global, cube local: An Earth Observation Data Cube’s contribution to the Digital Earth vision. Big Earth Data, 7(3), 831–859. https://doi.org/10.1080/20964471.2022.2099236